1. Field of the Invention
The present invention relates to speech recognition models and, more particularly, to composite acoustic models used for speech recognition for specific tasks.
2. Description of the Related Art
Speech recognition systems are used in many areas today to transcribe speech into text. The success of this technology in simplifying man-machine interaction is stimulating the use of this technology into a plurality of useful applications, such as transcribing dictation, voicemail, home banking, directory assistance, etc. Though it is possible to design a generic speech recognition system and use it in a variety of different applications, it is generally the case that a system is tailored to the particular application being addressed. In this way, a more efficient system having better performance is realized.
Typical speech recognition systems include three components, an acoustic model that models the characteristics of speech, a language model that models the characteristics of language and a vocabulary that includes words that are relevant to that application. Some applications require a large vocabulary, for example voicemail transcription, because a voicemail message could be related to any topic. However, some applications, such as home banking are likely to have a smaller vocabulary since a smaller set of possible transactions and therefore words are used. Depending on the application, some words may be more important than others. For example, in home banking, digit recognition is more important since personal identification numbers and transaction amounts must be correctly recognized. Hence, the word error performance in recognizing digits is more important than the remainder of the vocabulary.
Therefore, a need exists for a speech recognition system and method for providing improved performance on an application specific subset of words. A further need exists for a system and method capable of providing speech recognition of non-task specific speech along with task specific speech to form a task specific composite model. A still further need exists for a task specific model that is easily constructed and needs only a limited amount of training data for training it parameters.